Equatorial Guinea vs Somalia: Carbon stocks in living biomass (in forests), Millions of Metric
Equatorial Guinea
302.97
in 2023
Somalia
354.53
in 2023
Equatorial Guinea rank
75th
Somalia rank
74th
Carbon stocks in living biomass (in forests), Millions of Metric over time
- Equatorial Guinea
- Somalia
How they compare
Somalia currently reports 354.53 against 302.97 in Equatorial Guinea, a difference of 51.56.
That makes Somalia's figure about 1.2 times Equatorial Guinea's.
Across all 32 years both countries report, Somalia has been ahead every year.
Equatorial Guinea ranks 75th and Somalia ranks 74th of 198 countries.
Somalia has averaged higher in every one of the 4 decades both report.
Head to head by decade
| Decade | Equatorial Guinea | Somalia | Difference | Ahead |
|---|---|---|---|---|
| 1990s | 331.7 | 484.67 | 152.97 | Somalia |
| 2000s | 322.3 | 442.08 | 119.78 | Somalia |
| 2010s | 311.85 | 394.75 | 82.91 | Somalia |
| 2020s | 304.53 | 361.63 | 57.09 | Somalia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher carbon stocks in living biomass (in forests), millions of metric, Equatorial Guinea or Somalia?
- Somalia, at 354.53 against 302.97 in Equatorial Guinea as of 2023.
- What is the difference in carbon stocks in living biomass (in forests), millions of metric between Equatorial Guinea and Somalia?
- 51.56, with Somalia ahead.
- How many years of comparable data are there for Equatorial Guinea and Somalia?
- 32 years are reported by both, from 1992 to 2023.
- How do Equatorial Guinea and Somalia rank globally for carbon stocks in living biomass (in forests), millions of metric?
- Equatorial Guinea ranks 75th and Somalia ranks 74th of 198 countries.
- Where does this data come from?
- International Monetary Fund, published as Carbon stocks in living biomass (in forests), Millions of Metric Tonnes (Not Applicable). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
This dataset provides information on global climate and weather patterns, providing insights into temperature variations, land cover accounts, and shifts in mean sea levels.